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In the finetune phase, the whole dataset is used which will cause over fitting for the model...
So, I think this can be solved by:
- divide the dataset into training, test & validation sets
- Or, usin…
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Dear rjpg,
Is AutoEncoderMNIST.py a stacked autoencoder? Could you please provide clarification on that?
Thanks.
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TFLearn is awesome, thanks for putting it together.
I am trying to work out how to create a stacked autoencoder architecture do you have a pattern or example where you have done anything similar? I h…
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NNet Models
- Template + Module based Framework
- Feedforward and back-propagation (BP)
- Sparse Autoencoder
- Stacked Autoencoder
Utilities
- Objective templates: L1/L2 norm, softmax, ...
- Trainin…
bobye updated
10 years ago
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A layer-wise training method for the convolutional autoencoder is used in (Masci, Jonathan, et al. "Stacked convolutional auto-encoders for hierarchical feature extraction." Artificial Neural Networks…
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# References
+ [Introduction To Autoencoders In Machine Learning](https://youtu.be/NZ97-lFEUq8)
+ [Convolutional autoencoder for image denoising](https://keras.io/examples/vision/autoencoder/)
+ [B…
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I am implementing this code on my biological datasets. When I run the code multiple times, it produces quite different results. The ARIs vary from 0.4 to 0.8. I find out that the pretrained model ma…
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Correct me if I am wrong, the current implementation does not seem to be trained layer-by-layer. I've been searching for examples for stacked autoencoders trained in layerwise fashion using Keras. Any…
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I just try with the file after a slight modifying for my custom data **run_stacked_autoencoder_supervised.py** with doc configuation
After running the code the output shows always test accuracy …
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Please correct me if I am wrong: Stacked Denoising Autoencoder needs to be trained layerwise upto my knowledge. I cannot see the code written in this fashion. Please correct me if I am missing on some…